Implementation:Langchain ai Langchain ModelLaboratory

Knowledge Sources	Langchain_ai_Langchain
Domains	Model Comparison, Experimentation
Last Updated	2026-02-11 00:00 GMT

Overview

ModelLaboratory is a utility class for experimenting with and comparing the output of different LLM models or chains side by side on the same input.

Description

ModelLaboratory lives in the langchain_classic package and provides a convenient way to run the same input through multiple chains (or LLMs) and compare their outputs visually in the terminal. It supports initialization from either a list of Chain objects or a list of BaseLLM objects (via the from_llms class method). Each chain must have exactly one input and one output variable. Outputs are color-coded for easy visual comparison.

Usage

Import this class when you want to compare the behavior of different models or chains against the same prompt input during experimentation and prototyping.

Code Reference

Source Location

• Repository: Langchain_ai_Langchain
• File: libs/langchain/langchain_classic/model_laboratory.py
• Lines: 1-99

Signature

class ModelLaboratory:
    def __init__(
        self,
        chains: Sequence[Chain],
        names: list[str] | None = None,
    ) -> None: ...

    @classmethod
    def from_llms(
        cls,
        llms: list[BaseLLM],
        prompt: PromptTemplate | None = None,
    ) -> ModelLaboratory: ...

    def compare(self, text: str) -> None: ...

Import

from langchain_classic.model_laboratory import ModelLaboratory

I/O Contract

Inputs

Name	Type	Required	Description
chains	Sequence[Chain]	Yes	A sequence of chains to experiment with. Each must have exactly one input and one output variable.
names	None	No	Optional list of display names corresponding to each chain.
llms	list[BaseLLM]	Yes (for from_llms)	A list of LLMs to experiment with.
prompt	None	No	Optional prompt template to use with the LLMs (used by from_llms).
text	str	Yes (for compare)	Input text to run all models on.

Outputs

Name	Type	Description
compare output	None	Prints color-coded model outputs to stdout for visual comparison.
from_llms return	ModelLaboratory	A new instance initialized with LLM chains.

Usage Examples

Basic Usage

from langchain_classic.model_laboratory import ModelLaboratory
from langchain_core.prompts.prompt import PromptTemplate

# Initialize from LLMs
lab = ModelLaboratory.from_llms([llm1, llm2, llm3])

# Compare outputs
lab.compare("What is the meaning of life?")
# Prints color-coded outputs from each model

# Initialize with custom chains and names
lab = ModelLaboratory(chains=[chain1, chain2], names=["GPT-4", "Claude"])
lab.compare("Explain quantum computing")

Related Pages

• Heuristic:Langchain_ai_Langchain_Warning_Deprecated_Langchain_Classic
• Depends on langchain_classic.chains.base.Chain and langchain_classic.chains.llm.LLMChain